code: def google_bleu(y_true, y_predicted):
      return compute_bleu(
          ([y_t.lower().split()] for y_t in y_true),
          (y_p.lower().split() for y_p in y_predicted),
      )[0]
  
file_path: DeepPavlov/deeppavlov/metrics/bleu.py
imports: import itertools
  from typing import List, Tuple, Any
  from nltk.translate.bleu_score import corpus_bleu, sentence_bleu, SmoothingFunction, brevity_penalty, closest_ref_length
  from deeppavlov.core.common.metrics_registry import register_metric
  from deeppavlov.metrics.google_bleu import compute_bleu
label_desc: Use image node_id 3 for calling a global function with example usage: google_bleu(y_true, y_predicted) and returns: compute_bleu